Classification of haploid and diploid maize seeds by using image processing techniques and support vector machines

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dc.authorscopusid57203166786
dc.authorscopusid54882441600
dc.authorscopusid57203173453
dc.authorscopusid57203167226
dc.contributor.authorAltuntas Y.
dc.contributor.authorKocamaz A.F.
dc.contributor.authorCengiz R.
dc.contributor.authorEsmeray M.
dc.date.accessioned2024-08-04T20:04:01Z
dc.date.available2024-08-04T20:04:01Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.descriptionAselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netasen_US
dc.description26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780en_US
dc.description.abstractIn vivo maternal haploid technique is now widely used in advanced maize breeding programs. This technique shortens the breeding period and increases the efficiency of breeding. One of the important processes in this breeding technique is the selection of haploid seeds. The fact that this selection is performed manually reduces the selection success and causes time and labor loss. For this reason, it is a need to develop automatic selection methods that will save time and labor and increase selection success. In this study, a method was proposed to classify haploid and diploid maize seeds by using image processing techniques and support vector machines. Firstly, each maize seed is segmented from its original image. Secondly, five different features were extracted for each maize seed. Finally, obtained features vector is classified by using support vector machines. The proposed method performance was tested by 10-fold cross-validation method. As a result of the test, the success rate of haploid maize seed classification was calculated as 94.25% and the success rate of diploid maize seed classification was 77.91%. © 2018 IEEE.en_US
dc.identifier.doi10.1109/SIU.2018.8404800
dc.identifier.endpage4en_US
dc.identifier.isbn9781538615010
dc.identifier.scopus2-s2.0-85050805281en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2018.8404800
dc.identifier.urihttps://hdl.handle.net/11616/92292
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof26th IEEE Signal Processing and Communications Applications Conference, SIU 2018en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassificationen_US
dc.subjectHaploiden_US
dc.subjectImage processingen_US
dc.subjectMaizeen_US
dc.subjectSupport vector machinesen_US
dc.titleClassification of haploid and diploid maize seeds by using image processing techniques and support vector machinesen_US
dc.title.alternativeHaploid ve diploid misir tohumlarinin görüntü işleme teknikleri ve destek vektör makineleri kullanilarak siniflandirilmasien_US
dc.typeConference Objecten_US

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